Dataset for 'Prediction of Core Body Temperature from Multiple Variables' and 'The physiological strain index does not reliably identify individuals at risk of reaching a thermal tolerance limit' PROSPIE project

These are datafiles for two papers. The first tried to develop prediction equations for body core temperature based on non-invasive measurement. The second analyses the PSI, the Physiological Strain Index, and evaluates whether this has predictive power for people dropping out from work in the heat.

Below the abstracts of the two papers:

Prediction of Core Body Temperature from Multiple Variables

This paper aims to improve the prediction of rectal temperature (T_re) from insulated skin temperature (T_is) and micro-climate temperature (T_mc) previously reported (Richmond et al., Insulated skin temperature as a measure of core body temperature for individuals wearing CBRN protective clothing. Physiol Meas 2013; 34:1531–43.) using additional physiological and/or environmental variables, under several clothing and climatic conditions. Twelve male (25.8±5.1 years; 73.6±11.5kg; 178±6cm) and nine female (24.2±5.1 years; 62.4±11.5kg; 169±3cm) volunteers completed six trials, each consisting of two 40-min periods of treadmill walking separated by a 20-min rest, wearing permeable or impermeable clothing, under neutral (25°C, 50%), moderate (35°C, 35%), and hot (40°C, 25%) conditions, with and without solar radiation (600W m⁻²). Participants were measured for heart rate (HR) (Polar, Finland), skin temperature (T_s) at 11 sites, T_is (Grant, Cambridge, UK), and breathing rate (f) (Hidalgo, Cambridge, UK). T_mc and relative humidity were measured within the clothing. T_re was monitored as the ‘gold standard’ measure of T_c for industrial or military applications using a 10cm flexible probe (Grant, Cambridge, UK). A stepwise multiple regression analysis was run to determine which of 30 variables (T_is, T_s at 11 sites, HR, f, T_mc, temperature, and humidity inside the clothing front and back, body mass, age, body fat, sex, clothing, Thermal comfort, sensation and perception, and sweat rate) were the strongest on which to base the model. Using a bootstrap methodology to develop the equation, the best model in terms of practicality and validity included T_is, T_mc, HR, and ‘work’ (0 = rest; 1 = exercise), predicting T_re with a standard error of the estimate of 0.27°C and adjusted r² of 0.86. The sensitivity and specificity for predicting individuals who reached 39°C was 97 and 85%, respectively. Insulated skin temperature was the most important individual parameter for the prediction of T_re. This paper provides novel information about the viability of predicting T_c under a wide range of conditions, using predictors which can practically be measured in a field environment.

The physiological strain index does not reliably identify individuals at risk of reaching a thermal tolerance limit

PurposeThe physiological strain index (PSI) was developed to assess individuals’ heat strain, yet evidence supporting its use to identify individuals at potential risk of reaching a thermal tolerance limit (TTL) is limited. The aim of this study was to assess whether PSI can identify individuals at risk of reaching a TTL.MethodsFifteen females and 21 males undertook a total of 136 trials, each consisting of two 40–60 minute periods of treadmill walking separated by ~ 15 minutes rest, wearing permeable or impermeable clothing, in a range of climatic conditions. Heart rate (HR), skin temperature (Tsk), rectal temperature (Tre), temperature sensation (TS) and thermal comfort (TC) were measured throughout. Various forms of the PSI-index were assessed including the original PSI, PSIfixed, adaptive-PSI (aPSI) and a version comprised of a measure of heat storage (PSIHS). Final physiological and PSI values and their rate of change (ROC) over a trial and in the last 10 minutes of a trial were compared between trials completed (C, 101 trials) and those terminated prematurely (TTL, 35 trials).ResultsFinal PSIoriginal, PSIfixed, aPSI, PSIHS did not differ between TTL and C (p > 0.05). However, differences between TTL and C occurred in final Tsk, Tre–Tsk, TS, TC and ROC in PSIfixed, Tre, Tsk and HR (p < 0.05).ConclusionThese results suggest the PSI, in the various forms, does not reliably identify individuals at imminent risk of reaching their TTL and its validity as a physiological safety index is therefore questionable. However, a physiological-perceptual strain index may provide a more valid measure.